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Record W2127189756 · doi:10.1109/tpwrs.2006.873020

Design and Real-Time Implementation of Robust FACTS Controller for Damping Inter-Area Oscillation

2006· article· en· W2127189756 on OpenAlexaff
R. Majumder, Bikash C. Pal, Christian Dufour, Petr Korba

Bibliographic record

VenueIEEE Transactions on Power Systems · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsOpal-Rt Technologies (Canada)
FundersEngineering and Physical Sciences Research Council
KeywordsControl theory (sociology)Controller (irrigation)Robust controlTime domainElectric power systemOscillation (cell signaling)Power (physics)Set (abstract data type)Control engineeringRobustness (evolution)EngineeringLinear matrix inequalityCoupling (piping)Frequency domainComputer scienceControl systemControl (management)Mathematics

Abstract

fetched live from OpenAlex

An application of a normalized H/sub /spl infin// loop-shaping technique for design and simplification of damping controllers in the liner matrix inequalities (LMI) framework is illustrated in this paper. The solution is sought numerically using LMIs with additional pole-placement constraints. This ensures that the time-domain specifications are met besides robust stabilization. The designed control algorithm is implemented using a rapid prototyping controller. The performance of the controller is validated in real time using a detailed model of the power system implemented using Linux PC-based, multi-processor technology. The coupling between the controller and the power system is through a set of DAC and ADC modules in the analogue domain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.236
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations113
Published2006
Admission routes1
Has abstractyes

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